Pemodelan Regresi Spasial Data Panel

Studi Kasus : Indeks Pembangunan Manusia di Provinsi Kalimantan Timur Menurut Kabupaten/Kota Tahun 2017-2020

  • Endah Mulia Murdani Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • M Fathurahman Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • Rito Goejantoro Laboratorium Statistika Komputasi FMIPA Universitas Mulawarman

Abstract

Panel data is a combination of cross-section data and time-series data. The panel data regression can model the panel data. In its development, panel data regression has been developed to model spatial data, called panel data spatial regression. Spatial data is data that considers the empirical observations and considers the location factor of these observations. This study examines the spatial regression modeling of panel data and applies it to model the factors that influence the Human Development Index (HDI) of districts/cities in East Kalimantan Province from 2017 to 2020. HDI is a composite index that measures the average achievement in the three basic dimensions of human development that are considered very basic, namely life expectancy, knowledge, and a decent standard of living. HDI is one of the measuring tools considered to reflect the status of human development in a region and plays an essential role in improving the quality of human resources. The results show that the panel data spatial regression model suitable for modeling the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 is the Spatial Autoregressive Fixed Effect (SAR-FE) model. The rate of economic growth and the district/city minimum wage factors that significantly influence the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 based on the SAR-FE model is the rate of economic growth and the district/city minimum wage.


 


Keywords : Panel Data, Spatial Data, Panel Data Spatial Regression, SAR-FE, HDI

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References

Anselin, L. (1988). Spatial Econometrics: Method and Models. Dordrecht: Kluwer Academic Publisher.
Badan Pusat Statistik. (2018). Indeks Pembangunan Manusia 2017. Jakarta: Badan Pusat Statistik.
Badan Pusat Statistik. (2019). Indeks Pembangunan Manusia 2018. Jakarta: Badan Pusat Statistik.
Badan Pusat Statistik. (2020). Indeks Pembangunan Manusia 2019. Jakarta: Badan Pusat Statistik.
Badan Pusat Statistik. (2021). Indeks Pembangunan Manusia 2020. Jakarta: Badan Pusat Statistik.
Baltagi, B. H. (2005). Econometrics Analysis of Panel Data, 3rd Edition. Inc. New York: John Wilet & Sons Ltd.
Elhorst, J. (2003). Specification and Estimation of Spatial Panel Data Models. International Regional Science Review, 26(3), 244-268.
Fitrianto, A. & Musakkal, N. F. K. (2016). Panel Data Analysis for Sabah Construction Industries: Choosing the Best Model. Procedia Economics and Finance, 35, 241-248.
Ghozali, I. (2012). Aplikasi Analisis Multivariate dengan Program IMB SPSS. Yogyakarta: Universitas Diponegoro.
Greene, W. (2000). Econometrics Analysis, Third Edition. Inc. USA: Prentice Hall International.
Kementerian Kesehatan. (2014). Indeks Pembangunan Kesehatan Masyarakat. Jakarta: Badan Penelitian dan Pengembangan Kesehatan.
Kris, & Ana. (2019). Spatial Panel Random Effect untuk Indeks Pemabangunan Manusia di Daerah Istimewa Yogyakarta. Statistika Industri dan Komputasi, 4(2), 33-40.
Kutner, M. H., Nachtsheim, C. J., & Neter, J. (2004). Applied Linear Regression Models. New York: McGraw-Hill/Irwin.
Lesage, J. (1999). Spatial Econometrics . Morgantown: The Web Book of Regional Science Regional Research Institute, West Virginia University.
Lesage, J. P. (2009). Introduction to Spatial Econometrics. Boca Raton: Chapman & Hall/CRC.
Prasanti, T. W. (2015). Aplikasi Regresi Data Panel untuk Pemodelan Tingkat Pengangguran Terbuka Kabupaten/Kota di Provinsi Jawa Tengah. Gaussian, 4(3), 687-696.
Setiawan dan Dwi, E. (2010). Ekonometrika. Yogyakarta: Andi.
Published
2023-01-03
How to Cite
MURDANI, Endah Mulia; FATHURAHMAN, M; GOEJANTORO, Rito. Pemodelan Regresi Spasial Data Panel. EKSPONENSIAL, [S.l.], v. 13, n. 2, p. 179-188, jan. 2023. ISSN 2798-3455. Available at: <https://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/956>. Date accessed: 12 may 2024. doi: https://doi.org/10.30872/eksponensial.v13i2.956.
Section
Articles